Learning Phases

Step-by-Step Artificial Intelligence (AI) Roadmap

Phase 1: Python and Mathematics

Week 1-4

Python programming: data structures, functions, OOP
NumPy: arrays, vectorized operations, broadcasting
Pandas: DataFrames, data cleaning, merging, aggregation
Linear algebra: vectors, matrices, dot products, eigenvalues
Statistics: distributions, hypothesis testing, Bayes theorem

Outcome: Manipulate data proficiently with Python and understand the mathematical foundations that AI builds on.

Phase 2: Machine Learning Foundations

Week 5-9

Supervised learning: linear regression, logistic regression
Decision trees, random forests, and ensemble methods
Model evaluation: accuracy, precision, recall, F1, ROC-AUC
Cross-validation, bias-variance tradeoff, regularization
Feature engineering and feature selection techniques

Outcome: Build, evaluate, and improve machine learning models for classification and regression problems.

Phase 3: Deep Learning

Week 10-14

Neural network fundamentals: perceptrons, backpropagation, activation functions
TensorFlow/Keras or PyTorch: model building, training, evaluation
CNNs for image classification and object detection
RNNs, LSTMs, and sequence modeling basics
Transfer learning and pre-trained model fine-tuning

Outcome: Build deep learning models for image and text data using modern frameworks.

Phase 4: NLP and Generative AI

Week 15-19

Text preprocessing: tokenization, embeddings, TF-IDF
Transformers architecture and self-attention mechanism
Hugging Face: using pre-trained models for classification, NER, QA
LLMs: prompt engineering, RAG pipelines, fine-tuning basics
Building AI applications with LangChain or similar frameworks

Outcome: Build NLP applications and integrate large language models into practical AI solutions.

Phase 5: AI in Production

Week 20-24

Model deployment: Flask/FastAPI for serving predictions
MLOps basics: MLflow, experiment tracking, model versioning
Docker for containerizing AI applications
Cloud deployment: AWS SageMaker or Google Vertex AI basics
Ethics in AI: bias detection, fairness, and responsible AI

Outcome: Deploy AI models to production and understand the full lifecycle of AI applications.

Phase 6: Portfolio and Career Launch

Week 25-32

End-to-end AI project: problem definition to deployment
Kaggle competition participation for skill validation
Research paper reading and implementation practice
Resume building, GitHub AI portfolio, LinkedIn optimization
Mock interviews covering ML theory, coding, and system design

Outcome: Be job-ready as an AI Engineer with deployed projects, Kaggle experience, and interview preparation.

Training at CodingClave

CodingClave Covers This Entire Roadmap

You do not need to follow this roadmap alone. CodingClave Training Hub in Lucknow offers structured Artificial Intelligence (AI) training that covers every phase with live mentorship, doubt resolution, and real project-based learning.

28-Day Program

Phases 1-3

Foundations + first project. Ideal for summer training

45-Day Program

Phases 1-4

Deeper coverage + two projects. Great for industrial training

6-Month Program

All 6 Phases

Complete roadmap + job assistance. Best for internship program

All programs include live classes, hands-on projects, and a training certificate valid for AKTU/university submissions. The 6-month program includes mock interviews, resume building, and 100% job assistance with 50% fee after placement.

Frequently Asked Questions

Artificial Intelligence (AI) Roadmap — Common Questions

How long does it take to become an AI engineer?+

6-8 months of intensive study covering Python, mathematics, ML, deep learning, and deployment. CodingClave in Lucknow offers a structured 6-month AI program. Shorter programs (28/45 days) cover foundations.

Do I need a PhD to work in AI?+

No. Most industry AI roles require strong practical skills, not a PhD. B.Tech/M.Tech graduates with good projects and Kaggle experience get hired at top companies. Research roles may prefer advanced degrees.

Is math really necessary for AI?+

Yes, but you do not need to be a math expert. Understanding linear algebra, statistics, and calculus at a working level is essential. Our roadmap covers the required math alongside AI concepts.

Should I learn TensorFlow or PyTorch?+

PyTorch is more popular in research and increasingly in industry. TensorFlow has strong production tools. Our roadmap covers one in depth (typically PyTorch) with exposure to the other.

Does CodingClave cover this entire AI roadmap?+

Yes. The 6-month AI program at CodingClave in Lucknow covers all 6 phases from Python basics to deployment. The 28-day program covers Phases 1-2, and the 45-day covers Phases 1-3.

Can I get an AI job in Lucknow?+

Most AI roles are in Bangalore, Hyderabad, and Pune, but remote AI positions are growing rapidly. Lucknow-based developers can access remote AI roles paying ₹8-20 LPA through platforms like LinkedIn and Turing.

What projects should I build while learning AI?+

Start with a classification model (spam detection, sentiment analysis), then an image classifier with CNNs, then an end-to-end AI app with LLM integration and deployment.

Is AI a good career for B.Tech freshers?+

Excellent. AI engineer is one of the highest-paying fresher roles (₹4-10 LPA). The demand far exceeds supply. B.Tech CS/IT graduates from Lucknow with practical AI skills are highly competitive.

How does AI differ from machine learning?+

Machine learning is a subset of AI. AI is the broader field of making machines intelligent. ML specifically focuses on learning from data. Our roadmap covers both ML and broader AI concepts including deep learning and NLP.

What salary can I expect as a fresher AI engineer?+

₹4-10 LPA depending on skills, education, and company. In Lucknow, ₹4.5-8 LPA. Remote AI roles pay ₹8-20 LPA. AI consistently ranks among the highest-paying tech specializations.

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6 phases | Job-ready in 4-6 months with consistent daily practice

MERN Stack Learning Roadmap 2026

6 phases | Job-ready in 5-6 months with consistent daily practice

MEAN Stack Learning Roadmap 2026

6 phases | Job-ready in 5-7 months with consistent daily practice

Start Learning

Ready to Follow This Artificial Intelligence (AI) Roadmap?

Join CodingClave Training Hub in Lucknow for guided, practical-based Artificial Intelligence (AI) training. We cover this entire roadmap with live mentorship and real projects.

Apply Now WhatsApp Us View Artificial Intelligence (AI) Course

Artificial Intelligence (AI) Learning Roadmap 2026 — Beginner to Job-Ready

A structured, phase-by-phase guide to becoming a AI Engineer in 2026. This roadmap covers 6 phases from absolute beginner to job-ready in 6-8 months with consistent daily practice. Follow it self-paced or join CodingClave's Artificial Intelligence (AI) training in Lucknow for guided, practical-based learning.

Before You Start

Prerequisites for This Roadmap

Basic Python programming is helpful but not required
High school mathematics (algebra, basic statistics)
Curiosity about how machines learn and make decisions

Time to job-ready: 6-8 months with consistent daily practice

Learning Phases

Step-by-Step Artificial Intelligence (AI) Roadmap

Phase 1: Python and Mathematics

Week 1-4

Python programming: data structures, functions, OOP
NumPy: arrays, vectorized operations, broadcasting
Pandas: DataFrames, data cleaning, merging, aggregation
Linear algebra: vectors, matrices, dot products, eigenvalues
Statistics: distributions, hypothesis testing, Bayes theorem

Outcome: Manipulate data proficiently with Python and understand the mathematical foundations that AI builds on.

Phase 2: Machine Learning Foundations

Week 5-9

Supervised learning: linear regression, logistic regression
Decision trees, random forests, and ensemble methods
Model evaluation: accuracy, precision, recall, F1, ROC-AUC
Cross-validation, bias-variance tradeoff, regularization
Feature engineering and feature selection techniques

Outcome: Build, evaluate, and improve machine learning models for classification and regression problems.

Phase 3: Deep Learning

Week 10-14

Neural network fundamentals: perceptrons, backpropagation, activation functions
TensorFlow/Keras or PyTorch: model building, training, evaluation
CNNs for image classification and object detection
RNNs, LSTMs, and sequence modeling basics
Transfer learning and pre-trained model fine-tuning

Outcome: Build deep learning models for image and text data using modern frameworks.

Phase 4: NLP and Generative AI

Week 15-19

Text preprocessing: tokenization, embeddings, TF-IDF
Transformers architecture and self-attention mechanism
Hugging Face: using pre-trained models for classification, NER, QA
LLMs: prompt engineering, RAG pipelines, fine-tuning basics
Building AI applications with LangChain or similar frameworks

Outcome: Build NLP applications and integrate large language models into practical AI solutions.

Phase 5: AI in Production

Week 20-24

Model deployment: Flask/FastAPI for serving predictions
MLOps basics: MLflow, experiment tracking, model versioning
Docker for containerizing AI applications
Cloud deployment: AWS SageMaker or Google Vertex AI basics
Ethics in AI: bias detection, fairness, and responsible AI

Outcome: Deploy AI models to production and understand the full lifecycle of AI applications.

Phase 6: Portfolio and Career Launch

Week 25-32

End-to-end AI project: problem definition to deployment
Kaggle competition participation for skill validation
Research paper reading and implementation practice
Resume building, GitHub AI portfolio, LinkedIn optimization
Mock interviews covering ML theory, coding, and system design

Outcome: Be job-ready as an AI Engineer with deployed projects, Kaggle experience, and interview preparation.

Training at CodingClave

CodingClave Covers This Entire Roadmap

28-Day Program

Phases 1-3

Foundations + first project. Ideal for summer training

45-Day Program

Phases 1-4

Deeper coverage + two projects. Great for industrial training

6-Month Program

All 6 Phases

Complete roadmap + job assistance. Best for internship program

Frequently Asked Questions

Artificial Intelligence (AI) Roadmap — Common Questions

How long does it take to become an AI engineer?+

Do I need a PhD to work in AI?+

Is math really necessary for AI?+

Yes, but you do not need to be a math expert. Understanding linear algebra, statistics, and calculus at a working level is essential. Our roadmap covers the required math alongside AI concepts.

Should I learn TensorFlow or PyTorch?+

PyTorch is more popular in research and increasingly in industry. TensorFlow has strong production tools. Our roadmap covers one in depth (typically PyTorch) with exposure to the other.

Does CodingClave cover this entire AI roadmap?+

Yes. The 6-month AI program at CodingClave in Lucknow covers all 6 phases from Python basics to deployment. The 28-day program covers Phases 1-2, and the 45-day covers Phases 1-3.

Can I get an AI job in Lucknow?+

What projects should I build while learning AI?+

Start with a classification model (spam detection, sentiment analysis), then an image classifier with CNNs, then an end-to-end AI app with LLM integration and deployment.

Is AI a good career for B.Tech freshers?+

Excellent. AI engineer is one of the highest-paying fresher roles (₹4-10 LPA). The demand far exceeds supply. B.Tech CS/IT graduates from Lucknow with practical AI skills are highly competitive.

How does AI differ from machine learning?+

What salary can I expect as a fresher AI engineer?+

₹4-10 LPA depending on skills, education, and company. In Lucknow, ₹4.5-8 LPA. Remote AI roles pay ₹8-20 LPA. AI consistently ranks among the highest-paying tech specializations.

More Roadmaps

Explore Other Learning Roadmaps

PHP with Laravel Learning Roadmap 2026

6 phases | Job-ready in 4-6 months with consistent daily practice

Python with Django Learning Roadmap 2026

6 phases | Job-ready in 4-6 months with consistent daily practice

MERN Stack Learning Roadmap 2026

6 phases | Job-ready in 5-6 months with consistent daily practice

MEAN Stack Learning Roadmap 2026

6 phases | Job-ready in 5-7 months with consistent daily practice

Start Learning

Ready to Follow This Artificial Intelligence (AI) Roadmap?

Join CodingClave Training Hub in Lucknow for guided, practical-based Artificial Intelligence (AI) training. We cover this entire roadmap with live mentorship and real projects.

Apply Now WhatsApp Us View Artificial Intelligence (AI) Course